THE APPLICATION OF PYRAMID LUCAS-KANADE OPTICAL FLOW METHOD FOR TRACKING RAIN MOTION USING HIGH-RESOLUTION RADAR IMAGES

Short-duration rainfall characteristics in the form of certain intensity, time, and spatial distribution become valuable contribution for lahar flow disaster mitigation in a mountainous region. Due to mitigation purpose, such information can be provided through the rainfall nowcasting process. One of the promising rainfall nowcasting applications is the extrapolation-based method. Rain motion tracking is a crucial part of the rainfall nowcasting based on this method. This paper discusses the application of Pyramid Lucas-Kanade Optical Flow (PLKOF) method on the rain motion tracking analysis using 150x150m resolution radar image. The study of rain motion tracking is carried out using 112 successive rainfall images with 10-minutes time interval originating from Mt. Merapi X-band multiparameter radar. The rainfall movement patterns in short duration are presented in the displacement vector (u,v) images and scatter diagrams of rain motions at x- and y-directions. From the simulations, it was found that the average displacement of rain motions in the Mt. Merapi region is 9 pixels (8.3 km/h) with the dominant direction is northeast. The results show that PLKOF is relatively good at detecting small displacements, yet unable to identify the occurrence of rain growth and decay properly. The ability of PLKOF method in predicting the position of rain cell displacement is satisfied as indicated by the POD, CSI, and FAR indexes.

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A novel algorithm for ocean wave direction inversion from X-band radar images based on optical flow method

Acta Oceanologica Sinica ◽

10.1007/s13131-018-1201-9 ◽

2018 ◽

Vol 37 (3) ◽

pp. 88-93 ◽

Cited By ~ 2

Author(s):

Li Wang ◽

Yunfei Cheng ◽

Lijuan Hong ◽

Xinyu Liu

Keyword(s):

Optical Flow ◽

Ocean Wave ◽

Wave Direction ◽

Flow Method ◽

Radar Images ◽

Optical Flow Method ◽

X Band ◽

Novel Algorithm

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Feature Point Extraction and Motion Tracking of Cardiac Color Ultrasound under Improved Lucas–Kanade Algorithm

Journal of Healthcare Engineering ◽

10.1155/2021/4959727 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Xiaoli Zhang ◽

Punan Li ◽

Yibing Li

Keyword(s):

Optical Flow ◽

Speckle Tracking ◽

Motion Tracking ◽

Color Doppler ◽

Color Doppler Ultrasound ◽

Feature Points ◽

Sift Algorithm ◽

Calculation Time ◽

Tracking Method ◽

Optical Flow Method

The purpose of this research is to study the application effect of Lucas–Kanade algorithm in right ventricular color Doppler ultrasound feature point extraction and motion tracking under the condition of scale invariant feature transform (SIFT). This study took the right ventricle as an example to analyze the extraction effect and calculation rate of SIFT algorithm and improved Lucas–Kanade algorithm. It was found that the calculation time before and after noise removal by the SIFT algorithm was 0.49 s and 0.46 s, respectively, and the number of extracted feature points was 703 and 698, respectively. The number of feature points extracted by the SIFT algorithm and the calculation time were significantly better than those of other algorithms ( P < 0.01 ). The mean logarithm of the matching points of the SIFT algorithm for order matching and reverse order matching was 20.54 and 20.46, respectively. The calculation time and the number of feature points for the SIFT speckle tracking method were 1198.85 s and 81, respectively, and those of the optical flow method were 3274.19 s and 80, respectively. The calculation time of the SIFT speckle tracking method was significantly lower than that of the optical flow method ( P < 0.05 ), and there was no statistical difference in the number of feature points between the SIFT speckle tracking method and the optical flow method ( P > 0.05 ). In conclusion, the improved Lucas–Kanade algorithm based on SIFT significantly improves the accuracy of feature extraction and motion tracking of color Doppler ultrasound, which shows the value of the algorithm in the clinical application of color Doppler ultrasound.

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